Abstract #300613

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JSM 2003 Abstract #300613
Activity Number: 302
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #300613
Title: Quantile Regression with Clustered Survival Data
Author(s): Guosheng Yin*+ and Jianwen Cai
Companies: University of North Carolina, Chapel Hill and University of North Carolina
Address: 401 NC Highway 54, Carrboro, NC, 27510-2103,
Keywords: bootstrap ; clustered survival data ; estimating equation ; quantile regression ; perturbation ; prediction
Abstract:

As an alternative to the mean regression model, the quantile, especially the median, regression model has been studied extensively with independent failure time data under general random censorship. However, due to natural or artificial clustering, it is very common to encounter correlated failure time data in biomedical research where the intracluster correlation needs to be examined and adjusted accordingly. For clustered survival data under general random censorship, we study quantile regression models and propose an estimating equation approach for parameter estimation. The regression parameter estimates are shown to be asymptotically normally distributed. The variance-covariance estimation based on asymptotic approximation involves nonparametric functional density estimation. We apply and compare bootstrap and perturbation resampling methods for the estimation of the variance-covariance matrix. Simulation studies have been conducted to examine the finite sample properties. The new proposal is illustrated with a data from a clinical trial about ventilating tubes for otitis media.

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